Linear predictive coding (LPC) is a well-known and widely used method of speech coding. A known (LPC) technique is described below with reference to FIG. 1 of the accompanying drawings, which shows a known LPC encoder.
FIG. 1 is a block diagram of a known speech signal encoder, which utilizes linear predictive coding. The Incoming signal s(n) 100 is processed block by block in the encoder. The length N of the block is generally selected to be about 10 to 30 msec. The sampling frequency of speech signal 100 is generally 8 kHz, whereby a performance number in the order of 8 to 12 is obtained which is sufficient for the linear predictive coding model. The LPC parameters, which are indicative of the filter factors, are calculated for each block of the speech signal 100 in LPC analyzer 103. They can be factors a.sub.i ; i=1, 2, . . . , P of a direct-form filter type, where P is the prediction order used in the LPC model. The filters of the LPC model are often realized using a framework filter, for which the direct-form filter factors are converted into so-called reflection coefficients r.sub.ci, i=1, 2, . . . , P. The calculated filter factors are quantized and introduced to block 106 which carries out the multiplexing and error correction encoding.
Speech signal 100 to be encoded is introduced to the analysis filter 101 in such a way that each block of the speech signal 100 is filtered in analysis filter 101 by using those filter factor values that were calculated in the related block in the LPC analyzer 103. Quantized filter factors are employed in analysis filter 101 (even though unquantized values are available) in order to make its operation the reverse of that applied in the synthesis filtering used in decoding. The output of quantization block 104 is transferred to the dequantization block 105 and to analysis filter 101 to be used as filter factors. A so-called prediction error is obtained as an output of analysis filter 101 for each portion of the speech signal 100. This prediction error signal is quantized using quantizer 102 and it is also Introduced to multiplexer 106 to be transmitted to the telecommunications channel 107.
Several coding methods can be utilized depending on how the prediction error of the LPC model is transmitted to the decoder. When quantizing each sample separately of a prediction error, this is known as the Residual Excited Predictive Coding (REPC), see, for instance, U.S. Pat. No. 4,220,819. The most effective linear predictive coding methods employ the so-called analysis-synthesis technique, where a suitable quantized presentation is located for the prediction error by carrying out a synthesis of the speech signal in the encoder through different excitation options, i.e., quantized error signals, and by selecting the excitation which produces the best synthesis result for transmission to the decoder.
When searching for a representation for the prediction error which contains sample values which deviate from zero only by a small number of samples using the analysis-by-synthesis search, this is known as Multi Pulse Coding (MPC), see, for instance, U.S. Pat. No. 4 472 832. The Code Excited Linear Prediction (CELP), see, for instance, U.S. Pat. No. 4,817,152 employes, in turn, a vector presentation from each prediction error block, whereby the excitation optimized with the aid of the analysis-by-synthesis techniques may include a large number of non-zero sample values, the number of different excitation combinations being limited, at the same time, to the small number required by the low transmission rate, however.
The quality of the speech signal transmitted using LPC methods decreases considerably, if transmission errors occur in the transmission channel, especially in noisy channels such as those used in mobile radio communications. It is essential that the coding method used can overcome transmission errors as efficiently as possible if the best possible quality is to be achieved for the speech signal. It is possible to protect the coded speech signal against transmission errors by using a special error correction coding. In this case, in addition to parameters presenting the speech signal, additional bits used in error correction are transmitted to the receiver. However, the transmission of such additional error correction information decreases the number of bits available for the actual speech coding and thus increases the distortion of the speech signal caused by the speech coding itself. On the other hand, all the transmitted coding parameters cannot be effectively protected by the error correction coding.
Thus it would be desirable to achieve a decrease in the effect of the transmission errors which are caused by the coding parameters themselves especially if that decrease could be implemented without transmitting the additional information which decreases the channel capacity. This decrease in the effects of the transmission errors could either act as such or in combination with separate error correction coding.